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Multi-modal, multi-task, multi-attention (M3) deep learning detection of reticular pseudodrusen: towards automated and accessible classification of age-related macular degeneration.

Q. Chen, T. Keenan, A. Allot, Y. Peng, E. Agrón, A. Domalpally, C. Klaver, D. Luttikhuizen, M. Colyer, C. Cukras, H. Wiley, M. Magone, C. Cousineau-Krieger, W. Wong, Y. Zhu, E. Chew, and Z. Lu. CoRR, (2020)

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William Chew

Wakene Negassa Chewaka

Emily Solly

Emily Shen

Emily Troemer

Other publications of authors with the same name

Feature-based retinal image registration for longitudinal analysis of patients with age-related macular degeneration.T. Silva, N. Hotaling, E. Chew, and C. Cukras. Medical Imaging: Image Processing, volume 11313 of SPIE Proceedings, page 113132Z. SPIE, (2020)Device specific SD-OCT retinal layer segmentation using cycle-generative adversarial networks in patients with AMD.S. Mukherjee, T. Silva, G. Jayakar, P. Grisso, H. Wiley, T. Keenan, A. Thavikulwat, E. Chew, and C. Cukras. Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)Retinal layer segmentation for age-related macular degeneration patients with 3D-UNet.S. Mukherjee, T. Silva, G. Jayakar, P. Grisso, H. Wiley, T. Keenan, A. Thavikulwat, E. Chew, and C. Cukras. Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)Semi-supervised learning approach for automatic detection of hyperreflective foci in SD-OCT imaging.T. Silva, K. Heß, C. Duic, S. Mukherjee, H. Sandoval, J. Aduwo, T. Keenan, E. Chew, and C. Cukras. Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)MedGen: A Python Natural Language Processing Toolkit for Medical Text Processing.R. Yang, Q. Zeng, K. You, Y. Qiao, L. Huang, C. Hsieh, B. Rosand, J. Goldwasser, A. Dave, T. Keenan and 6 other author(s). CoRR, (2023)A deep learning approach for automated detection of geographic atrophy from color fundus photographs.T. Keenan, S. Dharssi, Y. Peng, Q. Chen, E. Agrón, W. Wong, Z. Lu, and E. Chew. CoRR, (2019)DeepSeeNet: A deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs.Y. Peng, S. Dharssi, Q. Chen, T. Keenan, E. Agrón, W. Wong, E. Chew, and Z. Lu. CoRR, (2018)Predicting myocardial infarction through retinal scans and minimal personal information.A. Diaz-Pinto, N. Ravikumar, R. Attar, A. Suinesiaputra, Y. Zhao, E. Levelt, E. Armellina, M. Lorenzi, Q. Chen, T. Keenan and 7 other author(s). Nat. Mach. Intell., 4 (1): 55-61 (2022)Multi-modal, multi-task, multi-attention (M3) deep learning detection of reticular pseudodrusen: towards automated and accessible classification of age-related macular degeneration.Q. Chen, T. Keenan, A. Allot, Y. Peng, E. Agrón, A. Domalpally, C. Klaver, D. Luttikhuizen, M. Colyer, C. Cukras and 7 other author(s). CoRR, (2020)Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.Q. Chen, T. Keenan, A. Allot, Y. Peng, E. Agrón, A. Domalpally, C. Klaver, D. Luttikhuizen, M. Colyer, C. Cukras and 7 other author(s). J. Am. Medical Informatics Assoc., 28 (6): 1135-1148 (2021)

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Disambiguation of "Chew, Emily Y."